Knowledge corroboration involves trying to exploit the “wisdom of the crowds” by using knowledge from many different people, organizations, committees, enterprises, automated systems or other entities. For example, a majority voting system is one example of knowledge corroboration where many people vote on an issue and the majority vote is used as the outcome.
Knowledge corroboration is difficult where the knowledge of the individuals to be corroborated is poor or very variable and where some individuals may act maliciously by reporting false information on purpose. In addition, in order to exploit knowledge corroboration, large scale systems are needed in order to corroborate knowledge from large numbers of entities. Providing knowledge corroboration solutions which are efficient and which scale up for use with huge amounts of data is difficult.
The embodiments described below are not limited to implementations which solve any or all of the disadvantages of known systems for knowledge corroboration.